In communications networks, there may be a challenge to obtain good performance and capacity for a given communications protocol, its parameters and the physical environment in which the communications network is deployed.
For example, future generations of wireless communications networks may provide ubiquitous high data-rate coverage. Currently emerging standards for wireless communications networks, such as Long Term Evolution Advanced (LTE-Advanced) from the 3rd Generation Partnership Project (3GPP), are targeted to support up to 1 Gbps in the downlink (from radio access network nodes to portable wireless devices) and 500 Mbps in the uplink (from portable wireless devices to radio access network nodes). Achieving such data rates requires a significant improvement in the experienced signal-to-interference-plus-noise ratio (SINR) at the receiver nodes. The use of multiple antennas at both the transmitter node and the receiver node is an interesting approach to provide a remarkable increase in the data rates and reliability of wireless transmission in a point-to-point scenario. However, in frequency reuse-1 wireless systems, in which multiple transmitter-receiver pairs (where one transmitter-receiver pair may consist of one radio access network node and one portable wireless device) operate concurrently and independently over the same time/frequency resources, the transmission between each transmitter-receiver pair commonly causes interference to neighboring transmitter-receiver pairs, resulting in a low experienced SINR at the receiver nodes. This may be crucial if the receiver node is farther from its desired transmitter node and closer to the interfering transmitter nodes. An embodiment of such a scenario is illustrated in FIG. 1.
FIG. 1 is a schematic illustration of intercell interference in a two-cell network 10 where each radio access network node 11a, 11b, (or base station, BS) serves a portable wireless device 14a, 14b (or user equipment, UE) in its own cell 12a, 12b using antenna arrays 15a, 15b to transmit transmission beams w(1) and w(2), respectively. More particularly, each BS transmits data in the downlink to a UE located at the cell boundary of its own cell on the same to time/frequency resource as the other BS. According to the illustrative example the UEs receive a severe intercell interference from the neighboring BS and hence experience a low SINR.
In general terms, beamforming is a technique for directional signal transmission and/or reception. With an array of multiple antennas it is, by using beamforming, possible to direct the wavefront in a specific direction by applying an appropriate weight at each antenna element. FIG. 2 schematically illustrates an antenna array 15a, 15b, 15c configured to transmit the signal x using N beam forming weights wi(θtilt), where i=1, . . . , N and where θtilt represent a tilting angle. In general terms, the overall radiation pattern of the antenna array is determined based on the number of antennas, their patterns, their relative positions, and their corresponding weights.
Consider now the two-cell communications network in FIG. 1. The complex-baseband received signal y at a desired UE can be written asy=Hswsxs+HIwIxl+n.   (1)
In (1), Hs denotes the desired channel state information (CSI) matrix between the antennas of the UE and those of the desired BS, while HI indicates the interfering CSI matrix between the antennas of the UE and those of the interfering BS. In addition, ws and wI are the beamforming vectors applied at the desired and interfering BSs, respectively, while xs and xI, denote the data symbols transmitted from the desired and interfering BSs, respectively. Finally, n represents additive white Gaussian noise.
In general terms the CSI matrix contains knowledge about radio propagation channel and antenna gains. This information describes, at least partially, how a signal propagates from a transmitter to a receiver. Hence, obtaining CSI enables the BS to perform efficient transmission towards an intended UE by dynamically adapting to the current channel conditions, and/or to suppress the interference towards a non-intended UE. This may be crucial for achieving reliable communication with high data rates in any to communications network.
In order to describe different beamformers, it is assumed that each transmission point j has the possibility to individually apply one of a finite number of beamformers that are indexed as b=1, 2, . . . , B. Hence, for the ease of notation, the b-th beamformer of the j-th transmission point is denoted wb(j). One example of beamforming, in the case of downlink transmission, is illustrated in FIG. 3. As can be seen in FIG. 3, the BS 11a, corresponding to transmission point j, is able to perform beam selection between three different beams w1(j), w2(j), and w3(j), corresponding to b=1, 2, 3. Furthermore, the BS is illustrated as currently transmitting using the beamformer w2(j) ) which results in the peak of the BS's main beam to be directed towards the illustrated portable wireless device 14a. In this case the UE 14a receives a stronger signal from the BS compared to the case where either of the beamformers w1(j) or w3(j) is used.
One approach to enhance the SINR over the cell area is to use the so-called coordinated multipoint transmission (CoMP). In CoMP multiple geographically separated transmission/reception nodes coordinate their transmission/reception to improve the coverage of high data rates, and/or to increase the cell-edge and average throughput. In particular, one goal is to distribute the UE perceived performance more evenly in the network by taking control of the interference in the network, either by reducing the interference and/or by better prediction of the interference.
In one simple form of CoMP, commonly denoted as coordinated beamforming, each UE communicates with its serving BS, exactly as in conventional cellular wireless networks (i.e., cellular wireless networks not based on CoMP). However, the design of beamformers is dynamically coordinated between different serving BSs in order to reduce the intercell interference caused by different transmissions occurring over the same time/frequency resources.
CoMP operation targets many different deployments, including coordination between sites and sectors in cellular macro deployments, as well as different configurations of so-called heterogeneous deployments, where for instance a macro radio access network node coordinates the transmission/reception with pico radio access network nodes within the macro coverage area. The coordination can be either distributed, by means of direct communication between the different radio access network nodes, or centralized, by using a central coordinating network node.
In the current state-of-the-art, the intercell interference suppression at each BS may be achieved by designing the beamformers such that the intercell interference leakage over the interfering CSI channel becomes as small as possible. In general terms, controlling the intercell interference in this way relies highly on the availability of accurate knowledge of both desired and interfering CSI matrices from all UEs in the network at each BS.
In practice, CSI acquisition at the BSs might require several phases such as training, estimation, feedback, and exchange over backhaul. In some scenarios such as high-speed UEs, the CSI changes too fast to be estimated or predicted accurately. Even when the CSI estimation/prediction is accurate, the impairments in the feedback/backhaul links (error, delay, etc.) can severely degrade the quality of the acquired CSI. With erroneous CSI, each BS designs its beamformer to mitigate the intercell interference over erroneous channels (instead of the true channels) and hence might result in severe interference leakage over the true channels.
Hence, there is still a need for an improved coordination of transmission from BSs in order to mitigate intercell interference leakage.